This template builds an AI-powered Movie Finder assistant connected to Telegram. It can identify movies from user text, screenshots, or other files by combining Google Gemini and BrowserAct’s “AI Film Finder Bot: Smart Scene & Concept Identification” workflow.

Text route: When a user sends a message, the scenario checks whether it looks like a movie description. Valid inputs are rewritten by Gemini into a clean, structured description. The bot sends this refined text back to the user, then calls the BrowserAct Film Finder workflow with the description (and optional FilmFinder / Google URLs). BrowserAct searches the web, returns a JSON list of candidate movies and summaries, and Gemini turns that JSON into a friendly “movie analysis” block that is sent back to Telegram.

File route: When a user sends an image or other attachment, the file is downloaded from Telegram and uploaded to Gemini. After a short delay to allow processing, Gemini analyzes the visual content and produces a single, compact paragraph describing the scene. That paragraph is then used in the same Film Finder workflow to search for matching movies, and the final results are again summarized by Gemini and returned to the chat.

This template is ideal for building a conversational movie assistant or recommendation bot that can understand either written descriptions or visual clues and reply with likely movies, short summaries, and optional similar-title suggestions—fully formatted for Telegram.